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Comparison between Deep Learning & Machine Learning

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All of a sudden every one is talking about them – irrespective of whether they understand the differences or not! Whether you have been actively following data science or not – you would have heard these terms. If you have often wondered to yourself what is the difference between machine learning and deep learning, read on to find out a detailed comparison in simple layman language. I have explained each of these term in detail. Then I have gone ahead to compare both of them and explained where we can use them.


Comparison between Deep Learning & Machine Learning

#artificialintelligence

All of a sudden every one is talking about them – irrespective of whether they understand the differences or not! Whether you have been actively following data science or not – you would have heard these terms. If you have often wondered to yourself what is the difference between machine learning and deep learning, read on to find out a detailed comparison in simple layman language. I have explained each of these term in detail. Then I have gone ahead to compare both of them and explained where we can use them. Let us start with the basics – What is Machine Learning and What is Deep Learning.


Theoretical Comparisons of Positive-Unlabeled Learning against Positive-Negative Learning

Neural Information Processing Systems

In PU learning, a binary classifier is trained from positive (P) and unlabeled (U) data without negative (N) data. Although N data is missing, it sometimes outperforms PN learning (i.e., ordinary supervised learning). Hitherto, neither theoretical nor experimental analysis has been given to explain this phenomenon. In this paper, we theoretically compare PU (and NU) learning against PN learning based on the upper bounds on estimation errors. We find simple conditions when PU and NU learning are likely to outperform PN learning, and we prove that, in terms of the upper bounds, either PU or NU learning (depending on the class-prior probability and the sizes of P and N data) given infinite U data will improve on PN learning.


Top 5 Books on AI and ML to Grab Today

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It has been popularly noted that artificial intelligence would be like the ultimate version of Google. With recent advancements in research and technology, Artificial Intelligence (AI) and Machine Learning (ML) are slowly becoming a part of our routine. The pace at which technology is growing is unfathomable. As these smart technologies engulf our life, staying updated with them is the need of the day. So, here's Packt's selection of finest books in artificial intelligence and machine learning that will help you have an edge in these fields: Reinforcement Learning is the trending and one of the most promising branches of artificial intelligence.


insideBIGDATA Guide to Artificial Intelligence & Deep Learning

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Artificial Intelligence & Deep Learning is transforming the entire world of technology, but AI isn't new. It has been around for decades, but AI technologies are only making headway now due to the proliferation of data and the investments being made in storage, compute and analytics technologies. Much of this progress is due to the ability of learning algorithms to spot patterns in larger and larger amounts of data. In this insideBIGDATA Guide to Artificial Intelligence & Deep Learning, we provide an in depth look at AI and deep learning in terms of how it's being used and what technological advances have made it possible. Artificial Intelligence is an amazing tool set that is helping people create exciting applications and creating new ways to service customers, cure diseases, prevent security threats, and much more.